International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

Frequency: 12

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 Volume 12, Issue 9 (September 2025), Pages: 107-117

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 Original Research Paper

Examining student acceptance of Procreate in digital art education using the technology acceptance model (TAM)

 Author(s): 

 Xu Ying 1, 2, Siti Shukhaila Binti Shaharuddin 1, *, Sharulnizam Bin Ramli 1, Yao Heng 3, Gao Nannan 1

 Affiliation(s):

  1Faculty of Creative Technology and Heritage, Universiti Malaysia Kelantan, Kota Bharu, Malaysia
  2Faculty of Fine Arts, Design and Architecture, Zhuhai College of Science and Technology, Zhuhai, China
  3Chengdu Academy of Fine Arts, Sichuan Conservatory of Music, Chengdu, China

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 * Corresponding Author. 

   Corresponding author's ORCID profile:  https://orcid.org/0000-0001-9076-1206

 Digital Object Identifier (DOI)

  https://doi.org/10.21833/ijaas.2025.09.010

 Abstract

This study employs the Technology Acceptance Model (TAM) to explore students’ acceptance of Procreate in educational settings, focusing on the relationships between perceived ease of use (PEOU), perceived usefulness (PU), and behavioral intention to use (BIU). A cross-sectional survey was conducted among university students enrolled in art and design programs. Data were collected through an online questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The findings reveal significant positive relationships among the variables, with PEOU showing strong direct effects on BIU (β = 0.494, p < 0.001) and PU (β = 0.500, p < 0.001), while PU also positively influenced BIU (β = 0.205, p < 0.001). The model demonstrated a good fit (SRMR = 0.038, NFI = 0.947) and high reliability (Cronbach’s alpha > 0.90 for all constructs), confirming the framework’s robustness. These results contribute to understanding technology adoption in creative education and provide practical implications for educators, software developers, and institutional decision-makers. The study underscores the importance of usability in educational technology design, suggesting that prioritizing user-friendly interfaces can enhance student engagement and adoption of digital art tools.

 © 2025 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords

 Technology acceptance model, Digital art tools, Usability, Creative education, Student engagement

 Article history

 Received 7 March 2025, Received in revised form 21 July 2025, Accepted 12 August 2025

 Acknowledgment

No Acknowledgment. 

 Compliance with ethical standards

 Ethical considerations

Participation was entirely voluntary, and informed consent was obtained from all respondents prior to data collection. Anonymity and confidentiality were assured, and no identifying personal information was collected.

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Ying X, Shaharuddin SSB, Ramli SB, Heng Y, and Nannan G (2025). Examining student acceptance of Procreate in digital art education using the technology acceptance model (TAM). International Journal of Advanced and Applied Sciences, 12(9): 107-117

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 Figures

  Fig. 1

 Tables

  Table 1  Table 2  Table 3  Table 4  Table 5  Table 6  Table 7  Table 8  Table 9

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 References (37)

  1. Abdulrasul AH, Sallabi OM, and Elaish MM (2023). A proposed technology acceptance model for measuring cloud computing usage in education. In the 11th International Conference on Systems and Control, IEEE, Sousse, Tunisia: 252-257.  https://doi.org/10.1109/ICSC58660.2023.10449841    [Google Scholar]
  2. Ali I, Warraich NF, and Butt K (2024). Acceptance and use of artificial intelligence and AI-based applications in education: A meta-analysis and future direction. Information Development, 41(3): 859-874.  https://doi.org/10.1177/02666669241257206    [Google Scholar]
  3. Amir RIM, Mohd IH, Saad S, Abu Seman SA, and Tuan Besar TBH (2020). Perceived ease of use, perceived usefulness, and behavioral intention: The acceptance of crowdsourcing platform by using technology acceptance model (TAM). In: Kaur N and Ahmad M (Eds.), Charting a sustainable future of ASEAN in business and social sciences: 403-410. Springer, Singapore, Singapore.  https://doi.org/10.1007/978-981-15-3859-9_34    [Google Scholar]
  4. Anaam EA, Haw SC, Palanichamy N, Ali A, and Azni S (2023). Analysis of perceived usefulness and perceived ease of use in relation to employee performance. International Journal of Membrane Science and Technology, 10(2): 1607-1616.  https://doi.org/10.15379/ijmst.v10i2.1836    [Google Scholar]
  5. Chiu W, Badu‐Baiden F, and Cho H (2024). Consumers' intention to use online food delivery services: A meta‐analytic structural equation modeling approach. International Journal of Consumer Studies, 48(3): e13052.  https://doi.org/10.1111/ijcs.13052    [Google Scholar]
  6. Dash G and Chakraborty D (2021). Transition to e-learning: By choice or by force: A cross-cultural and trans-national assessment. Prabandhan: Indian Journal of Management, 14(3): 8-23.  https://doi.org/10.17010/pijom/2021/v14i3/158151    [Google Scholar]
  7. Davis FD (1989). Technology acceptance model: TAM. In: Al-Suqri MN and Al-Aufi AS (Eds.), Information seeking behavior and technology adoption, University of Michigan, Ann Arbor, USA.    [Google Scholar]
  8. Davis FD, Bagozzi RP, and Warshaw PR (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8): 982-1003.  https://doi.org/10.1287/mnsc.35.8.982    [Google Scholar]
  9. Dhingra M and Mudgal RK (2019). Applications of perceived usefulness and perceived ease of use: A review. In the 8th International conference system modeling and advancement in research trends, IEEE, Moradabad, India: 293-298.  https://doi.org/10.1109/SMART46866.2019.9117404    [Google Scholar]
  10. Eze NU, Obichukwu PU, and Kesharwani S (2021). Perceived usefulness, perceived ease of use in ICT support and use for teachers. IETE Journal of Education, 62(1): 12-20.  https://doi.org/10.1080/09747338.2021.1908177    [Google Scholar]
  11. Frøsig TB (2023). Expanding the technology acceptance model (TAM) to consider teachers needs and concerns in the design of educational technology (EdTAM). International Journal of Emerging Technologies in Learning, 18(16): 130-140.  https://doi.org/10.3991/ijet.v18i16.42319    [Google Scholar]
  12. González-Zamar MD and Abad-Segura E (2021). Digital design in artistic education: An overview of research in the university setting. Education Sciences, 11(4): 144.  https://doi.org/10.3390/educsci11040144    [Google Scholar]
  13. Granić A and Marangunić N (2019). Technology acceptance model in educational context: A systematic literature review. British Journal of Educational Technology, 50(5): 2572-2593.  https://doi.org/10.1111/bjet.12864    [Google Scholar]
  14. Gutierrez-Aguilar O, Ticona-Apaza F, Calliñaupa-Quispe G, Duche-Pérez A, Salas-Valdivia L, and Chicaña-Huanca S (2022). Ease of use and perceived usefulness and its influence on motivation, collaboration and behavioral intention in university students in times of COVID-19. In the XVII Latin American Conference on Learning Technologies, IEEE, Armenia, Colombia: 1-6.  https://doi.org/10.1109/LACLO56648.2022.10013372    [Google Scholar]
  15. Hair J, Hollingsworth CL, Randolph AB, and Chong AYL (2017). An updated and expanded assessment of PLS-SEM in information systems research. Industrial Management and Data Systems, 117(3): 442-458.  https://doi.org/10.1108/IMDS-04-2016-0130    [Google Scholar]
  16. Hua C and Yu M (2024). Innovations in art education: Analysing new teaching methods, technology integration, and unique curriculum designs reshaping art education in higher education institutions. In the 5th World Conference on Arts, Humanities, Social Sciences and Education, Vienna, Austria.  https://doi.org/10.62422/978-81-968539-1-4-048    [Google Scholar]  PMid:38548379 PMCid:PMC10978098
  17. Imenda S (2014). Is there a conceptual difference between theoretical and conceptual frameworks. Journal of Social Sciences, 38(2): 185-195.  https://doi.org/10.1080/09718923.2014.11893249    [Google Scholar]
  18. Kemp A, Palmer E, Strelan P, and Thompson H (2024). Testing a novel extended educational technology acceptance model using student attitudes towards virtual classrooms. British Journal of Educational Technology, 55(5): 2110-2131.  https://doi.org/10.1111/bjet.13440    [Google Scholar]
  19. Kline RB (2023). Principles and practice of structural equation modeling. 5th Edition, Guilford Publications, New York, USA.    [Google Scholar]
  20. Kumar JA, Bervell B, Annamalai N, and Osman S (2020). Behavioral intention to use mobile learning: Evaluating the role of self-efficacy, subjective norm, and WhatsApp use habit. IEEE Access, 8: 208058-208074.  https://doi.org/10.1109/ACCESS.2020.3037925    [Google Scholar]
  21. Machdar NM (2016). The effect of information quality on perceived usefulness and perceived ease of use. Business and Entrepreneurial Review, 15(2): 131-146.  https://doi.org/10.25105/ber.v15i2.4630    [Google Scholar]
  22. McCready M (2021). On born digital artwork, new drawing applications, and new opportunities. Visual Resources Association Bulletin, 48(2): 1.    [Google Scholar]
  23. Panergayo AAE and Aliazas JVC (2021). Students' behavioral intention to use learning management system: The mediating role of perceived usefulness and ease of use. International Journal of Information and Education Technology, 11(11): 538-545.  https://doi.org/10.18178/ijiet.2021.11.11.1562    [Google Scholar]
  24. Porkodi S and Tabash BKH (2024). A comprehensive meta-analysis of blended learning adoption and technological acceptance in higher education. International Journal of Modern Education and Computer Science, 16(1): 47-71.  https://doi.org/10.5815/ijmecs.2024.01.05    [Google Scholar]
  25. Pratiwi RT, Purwanto SK, and Nurhasanah N (2023). Impact of perceived usefulness, perceived ease of use and consumer trust on behavioral intention. Penanomics: International Journal of Economics, 2: 3.  https://doi.org/10.56107/penanomics.v2i3.152    [Google Scholar]
  26. Purnomo HS (2023). The implementation of technology acceptance model towards mobile photography application adobe lightroom. Jurnal Akuntansi, Manajemen dan Ekonomi, 25(3): 35-42.  https://doi.org/10.32424/1.jame.2023.25.3.6587    [Google Scholar]
  27. Putra RA, Ahmad S, and Rahman FM (2023). The influence of perceived usefulness and perceived ease of use on behavioral intention on BRImo application users in Bengkulu City. Journal of Consumer Studies and Applied Marketing, 1(1): 46-60.  https://doi.org/10.47191/jefms/v6-i12-18    [Google Scholar]
  28. Raksadigiri MW and Wahyuni S (2020). Perceived ease of use effect on perceived usefulness and attitude towards use and its impact on behavioural intention to use. International Journal of Advanced Research, 8(12): 439-444.  https://doi.org/10.21474/IJAR01/12167    [Google Scholar]
  29. Ridho A, Gusasi FF, Hasanuddin ADI, and Ibrahim SA (2022). The use of digital illustrators in histology practicum learning of medical students in Gorontalo: Perception study. Jambura Medical and Health Science Journal, 1(2): 90-97.  https://doi.org/10.37905/jmhsj.v1i2.16198    [Google Scholar]
  30. Rosa JC, Rêgo BBD, Garrido FA, Valente PD, Nunes NJ, and Matos E (2020). Interaction design and requirements elicitation integrated through SPIDe: A feasibility study. In the 19th Brazilian Symposium on Human Factors in Computing Systems, Association for Computing Machinery, Diamantina, Brazil: 1-10.  https://doi.org/10.1145/3424953.3426498    [Google Scholar]
  31. Scherer R, Siddiq F, and Tondeur J (2019). The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers' adoption of digital technology in education. Computers and Education, 128: 13-35.  https://doi.org/10.1016/j.compedu.2018.09.009    [Google Scholar]
  32. Seligman LS (2001). Perceived value impact as an antecedent of perceived usefulness, perceived ease of use, and attitude: A perspective on the influence of values on technology acceptance. Ph.D. Dissertation, The University of Texas, Austin, USA.    [Google Scholar]
  33. Sheppard M and Vibert C (2019). Re-examining the relationship between ease of use and usefulness for the net generation. Education and Information Technologies, 24: 3205-3218.  https://doi.org/10.1007/s10639-019-09916-0    [Google Scholar]
  34. Tang X, Zainal SRB M, and Li Q (2023). Multimedia use and its impact on the effectiveness of educators: A technology acceptance model perspective. Humanities and Social Sciences Communications, 10: 923.  https://doi.org/10.1057/s41599-023-02458-4    [Google Scholar]
  35. Tsai KC (2012). Play, imagination, and creativity: A brief literature review. Journal of Education and Learning, 1(2): 15-20.  https://doi.org/10.5539/jel.v1n2p15    [Google Scholar]
  36. Widiar G, Yuniarinto A, and Yulianti I (2023). Perceived ease of use's effects on behavioral intention mediated by perceived usefulness and trust. Interdisciplinary Social Studies, 2(4): 1829-1844.  https://doi.org/10.55324/iss.v2i4.397    [Google Scholar]
  37. Wiprayoga P, Gede S, and Suasana GAKG (2023). The role of attitude toward using mediates the influence of perceived usefulness and perceived ease of use on behavioral intention to use. Russian Journal of Agricultural and Socio-Economic Sciences, 140(8): 53-68.  https://doi.org/10.18551/rjoas.2023-08.06    [Google Scholar]